ArticleJournal of healthcare engineering2022
Unsupervised Data Mining and Effect of Fast Rehabilitation Nursing Intervention in Fracture Surgery.
Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Fast-track rehabilitation plus humanized nursing improves gastrointestinal function and quality of life in post-surgical gastric cancer patients.World journal of gastrointestinal surgery · 2025Article
- Clinical value of rehabilitation nursing after internal fixation of distal radius fractures.American journal of translational research · 2024Article
- Retracted: Unsupervised Data Mining and Effect of Fast Rehabilitation Nursing Intervention in Fracture Surgery.Journal of healthcare engineering · 2023Article
Corrections and comments
- Retraction · 2023-12-06Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
At present, the most commonly used surgical treatment for fractures caused by external force injury is clinical, and unsupervised data mining is more advantageous in the face of the unknown format of perioperative network data. Therefore, this research aims to explore the application effect of unsupervised data mining in the concept of rapid rehabilitation nursing intervention after fracture surgery. 80 patients who underwent fracture surgery in the Department of Orthopedics of XXX Hospital were determined as the subjects, who were rolled into a research group (group R, 40 cases) and a control group (group C, 40 cases) by drawing lots. An unsupervised data mining algorithm based on unsupervised data mining for support vector machines (VDMSVMs) was proposed and applied to two groups of patients undergoing perioperative fracture surgery with the rapid rehabilitation nursing intervention and basic routine nursing. The results showed that the number of important features selected by the VDMSVM algorithm (5) was obviously more than that of the compressed edge fragment sampling (CEFS) algorithm (1) and the multicorrelation forward searching (MCFS) algorithm (2) (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.